> For the complete documentation index, see [llms.txt](https://docs.feast.dev/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.feast.dev/untitled/tutorials.md). # Tutorials - [Sample use-case tutorials](https://docs.feast.dev/untitled/tutorials/tutorials-overview.md) - [Driver ranking](https://docs.feast.dev/untitled/tutorials/tutorials-overview/driver-ranking-with-feast.md): Making a prediction using a linear regression model is a common use case in ML. This model predicts if a driver will complete a trip based on features ingested into Feast. - [Fraud detection on GCP](https://docs.feast.dev/untitled/tutorials/tutorials-overview/fraud-detection.md): A common use case in machine learning, this tutorial is an end-to-end, production-ready fraud prediction system. It predicts in real-time whether a transaction made by a user is fraudulent. - [Real-time credit scoring on AWS](https://docs.feast.dev/untitled/tutorials/tutorials-overview/real-time-credit-scoring-on-aws.md): Credit scoring models are used to approve or reject loan applications. In this tutorial we will build a real-time credit scoring system on AWS. - [Driver stats on Snowflake](https://docs.feast.dev/untitled/tutorials/tutorials-overview/driver-stats-on-snowflake.md): Initial demonstration of Snowflake as an offline+online store with Feast, using the Snowflake demo template. - [Validating historical features with Great Expectations](https://docs.feast.dev/untitled/tutorials/validating-historical-features.md) - [Using Scalable Registry](https://docs.feast.dev/untitled/tutorials/using-scalable-registry.md): Tutorial on how to use the SQL registry for scalable registry updates - [Building streaming features](https://docs.feast.dev/untitled/tutorials/building-streaming-features.md) --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.feast.dev/untitled/tutorials.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.